Biology as a whole and proteomics in particular are moving towards the accurate quantification of large numbers of analytes in the context of specific experiments. In the case of proteomics, the analytes are typically peptides generated by tryptic digestion of protein samples. Systems biology experiments require accurate quantification of the same set of analytes over multiple samples, typically representing cells in differentially perturbed states. This stringent requirement derives from the long term goal of systems biology projects to generate mathematical models that simulate the system studied and make specific predictions about its behaviour under different conditions. While the comprehensive quantitative analysis of the transcriptome became readily accessible with the advent of the micro-array and other transcript profiling technologies, quantitative proteomic analyses to a similar depth and consistency are not achievable by the current proteomic approaches that are based on the generation of fragment ions from precursor ions selected automatically based on the precursor ion profiles (data dependent analysis, DDA). Besides their limited sensitivity, a main shortcoming of these methods is poor reproducibility of target selection which results in only partially overlapping protein sets if substantially similar samples are analyzed repeatedly. Such fragmentary data is also unsatisfactory for multiple applications beyond systems biology, e.g. biomarker discovery, in which complete quantification profiles for each element of a protein set in multiple samples are required. Therefore, new approaches are required which deliver precise quantitative data from defined sets of proteins reliably from multiple samples.
While gene expression analysis is a very mature technology, quantitative proteomics thus still suffers substantial technical limitations. The currently most used proteomics approaches are non-targeted, i.e. in each measurement they quasi-randomly sample a fraction of the proteome. Each repeat analysis required for comparing a proteome at different states, will sample only a subset of a set of proteins of interest, and not necessarily the same subset in each repeat, thus precluding the generation of complete datasets e.g. as when they are required for modelling biological systems. An additional limitation to a comprehensive proteomic analysis is the difficulty in detecting low abundant proteins. These limitations strongly affect the possibility to quantitatively measure key target proteins across different samples, e.g. in the context of biomedical, pharmacological or biological applications. Additionally they precluded so far the coverage of a whole proteome, in spite of the considerable efforts worldwide to identify complete proteomes.
Systems biology relies on data sets in which the same set of proteins is consistently identified and accurately quantified in multiple samples, a requirement that current shotgun approaches can therefore only partially meet. Selected/Multiple Reaction Monitoring (SRM/SRM) mass spectrometry is emerging as technology that ideally complements the discovery capabilities of shotgun proteomics by its unique potential for reliable and comprehensive quantification of substances of low abundance in complex samples.
Selected reaction monitoring (SRM) is a non-scanning mass spectrometry technique, performed on triple quadrupole-like instruments and in which collision-induced dissociation is used as a means to increase selectivity. In SRM experiments two mass analyzers are used as static mass filters, to monitor a particular fragment ion of a selected precursor ion. The specific pair of mass-over-charge (m/z) values associated to the precursor and fragment ions selected is referred to as a “transition” and can be written as parent m/z>fragment m/z (e.g. 673.5>534.3). Unlike common MS based proteomics, no mass spectra are recorded in a SRM analysis. Instead, the detector acts as counting device for the ions matching the selected transition thereby returning an intensity distribution over time. Multiple SRM transitions can be measured within the same experiment on the chromatographic time scale by rapidly toggling between the different precursor/fragment pairs (sometimes called multiple reaction monitoring, MRM). Typically, the triple quadrupole instrument cycles through a series of transitions and records the signal of each transition as a function of the elution time. The method allows for additional selectivity by monitoring the chromatographic coelution of multiple transitions for a given analyte. Although broadly used, the term multiple reaction monitoring to indicate the parallel acquisition of multiple SRM transitions might be in the future deprecated by the IUPAC nomenclature. The terms SRM/MRM are occasionally used also to describe experiments conducted in mass spectrometers other than triple quadrupoles (e.g. in trapping instruments) where upon fragmentation of a specific precursor ion a narrow mass range is scanned in MS2 mode, centered on a fragment ion specific to the precursor of interest or in general in experiments where fragmentation in the collision cell is used as a means to increase selectivity.
In this application the terms SRM and MRM or also SRM/MRM can be used interchangeably, since they both refer to the same mass spectrometer operating principle. For a matter of clarity we always use the term SRM throughout the text, but we always comprise both as well as any analogous technique, such as e.g. highly-selective reaction monitoring, hSRM, LC-SRM or any other SRM/MRM-like or SRM/MRM-mimicking approaches performed on any type of mass spectrometer and/or, in which the peptides are fragmented using any other fragmentation method such as e.g. CAD or ETD.
Triple quadrupole instruments operated in SRM mode have been used for decades to detect and quantify small molecules (e.g. drugs or drug metabolites extracted from complex biological matrices). The first applications of SRM for the quantification of proteins were targeting one or few selected peptides.
There is a particular demand for reliable high sensitivity quantification of proteins from plasma to bridge the current gap between biomarker candidate discovery and validation. The high dynamic range of more then 10 orders of magnitude of proteins in plasma from albumin (35-50 mg/ml) to low abundance proteins like interleukin 6 (0-5 pg/ml) challenges current technology.
Lange et al, (Molecular and Cellular Proteomics 7.8, 1489-1500) discloses the use of MRM to probe responses of some Streptococcus pyogenes proteins to the presence of human serum. In this paper a “real” biological sample (a mixture of Streptococcus proteome digests) was used to validate and optimize MRM assays. Therefore all known problems related to using biological samples are taken into account.
Mayya et al. (Molecular and Cellular Proteomics 5.6, 1146-1157) purified and accurately quantified heavy labelled synthetic peptides are used to develop MRM assays. These purified heavy labelled peptides are very expensive. The purity of the peptides used in the cited paper is described as >80% and they are quantified which makes them expensive.